Soil is a complex, living, changing and dynamic component of an agroecosystem. It is subject to alteration, and can be either degraded or wisely managed. A thorough understanding of the ecology of the soil ecosystem is a key part of designing and managing agroecosystems in which the long-term fertility and productive capacity of the soil is maintained, or even improved. Such an understanding begins with knowledge of how soil is formed in a given ecological region, and includes integration of all the components that contribute to the structure and function of the entire soil ecosystem. A great many biological, chemical and physical factors determine soil quality. By measuring some of these components and determining how they respond to management in an agricultural context, a foundation for assessing the health of the soil can be established. Ultimately, indicators of sustainability can be grounded in the assessment of soil conditions and how they change as a result of the choices a farmer makes in managing the agroecosystem. Three components of particular interest to farmers are soil pH, organic content (OC) and electrical conductivity.
Soil acidity or pH is a measure of the hydrogen ion (H+) activity in the soil solution, in this case water, and is specifically defined as the −log 10 of the hydrogen ion concentration. Soil pH will rise or fall depending on the impact of a range of factors, including farming practices. If as a result of these impacts the soil pH falls below or rises above certain optimum levels for biological and chemical activity, the soil will become much less productive
Organic matter plays many important roles in the soil ecosystem, all of which are of importance to sustainable agriculture. The organic content (OC) is one of the best indicators of soil quality, especially when the soil can be observed over a period of time. Measuring soil organic matter content with high precision and accuracy requires sophisticated equipment and involved techniques.
Finally, soil electrical conductivity (EC) is a measurement that correlates with soil properties that affect crop productivity, including soil texture, cation exchange capacity (CEC), drainage conditions, organic matter level, salinity, and subsoil characteristics.
The collection of soil property data related to these three components can be very costly and time consuming, and despite the criticality of the information, many fields go untested due to these cost and time commitments. This is a known and growing problem in agroecosystem management.
There are believed to be only four methods currently in use or under development to exam soil properties. Each of these four (4) systems uses a Cloud-based database to both accumulate examined data at varying situations and to build models for mapping calibration. The four known soil examination methods are:                1. Manual acquisition of soil samples from a field, and examining in a soil lab to obtain OM, EC, and pH data. These results can be uploaded to a Cloud-based database with an associate to the sampling position (GPS), administration location or a corresponding field number.        2. Automatic acquisition of soil samples from a field using a plurality of stationary base stations, each equipped with a mobile transmitter. Soil data is acquired through station soil sensors and transmitted from a station to a Cloud-based database. The data includes the known location and identification of each reporting station.        3. Veris Technologies (Salina, Kans.) manufactures and sells vehicle-mounted Soil Sensor Systems such as the MSP™ and MSP3™ with on-going soil sampling (for example, see http://www.veristech.com/the-sensors/msp). The sensor system is moved through a field (for example, via a farm tractor), while OM, EC, and pH sensor modules on the MSP™ allow a user to obtain data in an “on-the-go” fashion. The on-board software allows a user to determine how to acquire OM, EC, and pH on the field as the field is mapped to a preset grid of separate OM, EC, and pH grids respectfully (see FIG. 9). Data can be uploaded to a Cloud-based database for further calibration and analysis.        4. SoilOptix Technologies (http://www.practicalprecision.ca/solutions/soiloptix/) currently markets a passive sensor system mounted to the front of an ATV. The sensor system measures four nuclides that are naturally present in soil, including uranium, potassium-40, thorium and cesium. Data is collected, and variations in radiation levels are used to construct soil survey maps which are determine where the soil samples take place. With the soil sample confirmation, a group of soil texture maps are constructed which represent the standard N-P-K, OM, pH, etc.        
The first and second soil acquisition procedures take soil samples at a fix location. Manually taking samples requires experience to determine where to take soil samples (and possible average multiple samples to one) to send to a soil laboratory to examine a days' process. Conversely, automatically taking soil sample has ability to transit soil data to a Cloud-based database in minutes. However, mobility may have a much higher maintenance cost for sensors and other equipment and can be a slow, inefficient method for data collection, especially in large fields. While both procedures are in practice, neither is useful in solving all of the problems associated with field soil sampling and mapping.
MSP™ (see system No. 3 above) is a product made by the Veris Technologies. The device is moved through the field, and with a limited number of soil samples needed to calibrate, it can produce fairly accurate OM, EC, and pH measurement. The system of the present application uses this product to acquire soil properties in fields as determined by an aerial survey.
The SoilOptix™ (system No. 4 above) design has a passive sensor to collect gamma ray release through the top 12 inches of soil. However, due to very low energy emitting from the soil, it requires a fairly large amount of soil samples to build accurate database. With a sensor system mounted on an ATV, the process can be extremely slow and the coverage area may be further limited by the terrain of the land.
These and other problems are addressed by the present device and methods to provide a system and methods with numerous advantages in operation and effectiveness over prior art. The present invention uses an unmanned aerial vehicle (UAV) with a penetrating multispectral sensor to scan fields from the air. The system also uses MSP to acquire data and map the field by moving a sensor system through the field. A calibration is performed using soil sample results from predetermined locations based on the spectral image (survey). Finally, a mathematic module is used to calculate a correlation between the spectral image information and the grid of MSP soil properties, including OM, EC, and soil pH.